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We are seeking an experienced Principal Data Engineer to define, lead, and scale the technical strategy of our data platform. This is a senior, hands-on leadership role at the intersection of architecture, governance, and engineering excellence, where you will shape how data is collected, processed, and delivered across the organisation. You will own the end-to-end quality, performance, and scalability of our data systems — from raw ingestion through to trusted datasets powering business-critical analytics and reporting. This includes setting standard sand influencing the strategic roadmap for data infrastructure. Our stack is built on both AWS and Azure, using Databricks across data domains and you will lead the evolution of this ecosystem to meet future business needs. You’ll ensure that data is secure, compliant, discoverable, and business-ready, enabling analysts, data scientists, and stakeholders to make confident, data-driven decisions. This role is ideal for a highly technical leader who thrives at both the strategic and execution levels: someone equally comfortable defining architecture with executives, mentoring senior engineers, and optimising distributed pipelines at scale.
Job Responsibility:
Design and oversee scalable, performant, and secure architectures on Databricks and distributed systems
Anticipate scaling challenges and ensure platforms are future-proof
Lead the design and development of robust, high-performance data pipelines using PySpark and Databricks
Define and ensure testing frameworks for data workflows
Ensure end-to-end data quality from raw ingestion to curated, trusted datasets powering analytics
Establish and enforce best practices for data governance, lineage, metadata, and security controls
Ensure compliance with GDPR and other regulatory frameworks
Act as a technical authority and mentor, guiding data engineers
Influence cross-functional teams to align on data strategy, standards, and practices
Partner with product, engineering, and business leaders to prioritise and deliver high-impact data initiatives
Build a culture of data trust, ensuring downstream analytics and reporting are always accurate and consistent
Evaluate and recommend emerging technologies where they add value to the ecosystem
Requirements:
Broad experience as a Data Engineer including technical leadership
Broad cloud experience, ideally both Azure and AWS
Deep expertise in PySpark and distributed data processing at scale
Extensive experience designing and optimising in Databricks
Advanced SQL optimisation and schema design for analytical workloads
Strong understanding of data security, privacy, and GDPR/PII compliance
Experience implementing and leading data governance frameworks
Proven experience leading the design and operation of a complex data platform
Track record of mentoring engineers and raising technical standards
Ability to influence senior stakeholders and align data initiatives with wider business goals
Strategic mindset with a holistic view of data reliability, scalability, and business value
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